It is used to check the normality, heteroscedasticity and influential observations.
The diagnostic plot for multiple regression is a scatterplot of the prediction errors (residuals) against the predicted values and is used to see if the predictions can be improved by fixing problems in your data. Regression diagnostics plots can be created using the R base function plot() or the autoplot() function [ggfortify package], which creates a ggplot2-based graphics. The diagnostic plots show residuals in four different ways: Residuals vs Fitted. Used to check the linear relationship assumptions