What are the differences between Feature Interactions and Feature Importances?

Can someone intuitively explain how interacting variables are being handled by KNN.according to the book "Introduction to Data Mining": Nearest neighbor classifiers can handle the presence of interacting attributes, i.e., attributes that have more predictive power taken in combination then by themselves, by using appropriate proximity measures that can incorporate the effects of multiple attributes together. is there an example to help to demonstrate it? thank you