Binning is a data pre-processing technique used to reduce the effects of minor observation errors by transforming numerical data into categorical data. It involves dividing the range of a continuous variable into intervals or 'bins' and assigning each data point to a bin, which can simplify analysis and improve model performance by handling outliers and noise more effectively.