The Spatial Lag Model is a regression model used to account for spatial autocorrelation by incorporating the influence of neighboring observations into the dependent variable. It helps in understanding how the value of a variable in one location is affected by values in nearby locations, making it crucial for spatial data analysis in fields like economics, geography, and environmental science.