Variance inflation factor explains the correlation between the variables. In general, highly correlated do not any value to the model, infact they make the model interpretability low as well as increase the size of the model.

VIF is 1/ (1-R2) . Hence if all variables are completely uncorrelated, then VIF will be 1, if all variables are 100% correlated, then VIF will be infinite. As a rule of thumb, accept the variables if the VIF is below 1.5 (maybe relaxed to 2 in some cases).