Stochastic Regression Imputation is a statistical method used to handle missing data by predicting missing values based on a regression model, incorporating random error to preserve the natural variability of the data. This approach helps in maintaining the statistical properties of the dataset, thereby producing more reliable and unbiased estimates in subsequent analyses.