Nonlinear dimensionality reduction is a technique used to reduce the number of variables in a dataset while preserving its intrinsic structure, especially when the data lies on a nonlinear manifold. It is crucial for visualizing high-dimensional data and improving the performance of machine learning algorithms by mitigating the curse of dimensionality.