Nonparametric regression is a way to show how one thing is related to another without assuming a specific shape for the relationship. Instead of forcing the data to fit a certain pattern, this method lets the data itself determine how the relationship looks. Different techniques like kernel smoothing, local polynomial regression, and regression trees are used to create these relationships. When there are many factors involved, additive models are used to avoid issues caused by having too many variables.