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All have given unique perspectives to their answers, however the two answers that stand out from the rest are that of Rahul Garg and Dipankar Acharya. Rajesh's answer is a must read to understand the different types of noises.

The noise factors are the design or process parameters those are difficult or expensive to control and affect the output of variable of key interest negatively. On the other hand control factors are controllable factors and can be controlled by the person doing the process or experiment. For example : i) Say a farmer wants to grow the wheat, then the seed quality, time of sowing the seeds etc. are control factors and can be controlled by the farmer; however on the other hand outside temprature, humidity etc. are the noise factors which are difficult or expensive to control. ii) On the production floor, say itensity of the light impacts the productivity of the worker; then light intensity can be treated as the noise factor. How to overcome the effects of noise factors ? Effects of the noise factors can be reduced / eliminated by Blocking. We can divide the total population into homogenous groups called blocks. The logic behind making the blocks is the variation due to noise factors is less between the blocks and effect of the treatment is more clearly evident while we do the blocking. E.g. Say we want to calculate the productivity of the team and we think that shift timing is one of the noise factor that imapcts the team's productivity; so then we can calculate the team's productivity shift wise and address the problem effectively if it lies in a particular shift only. Compounding noise factors is also a strategy in which you group the noise factor levels into different combinations that you anticipate will result into the extreme response values. Because estimating the effects of individual noise factors is not the primary goal, compounding is a useful method to reduce the amount of testing. For example, if you have three noise factors, each factor with the two levels, you will have eight different combinations of settings to test. Instead, you may group noise factors into two overall settings – one setting in which the noise factors levels increase the response value and the other one in which the noise factors levels decrease the response value.

In Design of Experiments, we vary multiple Inputs (X's) at a time, in order to find the best combination of inputs to deliver the desired output (Y's). During the same, we may come across some parameters which are uncontrollable. These are called Noise factors. E.g. for an experiment on making the the right Dish, we can vary and control the quantities of constituents, temperature of cooking, time of cooking etc. But we cannot control factors like the mood of the Chef, the skills by which he mixes the dish etc. Mostly these human factors become noise and can affect the DOE results. Noise factors are of 2 types : Known and Unknown To address the same we can use 2 methods : a) Known Noise Factors : Use Blocking (A block is a group of homogenous experimental observations). b) Unknown Noise Factors : Use Randomization (make the Run order separate from Standard Order)