Collinearity refers to a statistical phenomenon where two or more predictor variables in a multiple regression model are highly linearly related, potentially leading to unreliable and unstable estimates of regression coefficients. It can inflate the variance of the coefficient estimates and make it difficult to determine the individual effect of each predictor variable on the dependent variable.