Mean subtraction is a preprocessing technique used in data normalization where the mean of the dataset is subtracted from each data point, centering the data around zero. This step is crucial in machine learning and data analysis as it helps in reducing bias and improving the convergence speed of algorithms by ensuring the data has zero mean, which can lead to more stable and efficient computations.