A Generalized Linear Model (GLM) is an extension of the traditional linear regression model that allows for response variables to have error distribution models other than a normal distribution. GLMs are used to model the relationship between a linear predictor function and a response variable, which can follow distributions such as binomial, Poisson, or gamma, making them versatile for various types of data analysis.