Nonparametric regression is a type of regression analysis that makes no assumptions about the form of the relationship between independent and dependent variables, allowing for more flexibility in modeling complex data patterns. It is particularly useful when the underlying data distribution is unknown or when the data exhibits nonlinear relationships that cannot be adequately captured by parametric models.