Nonlinear fitting is a statistical method used to model complex relationships between variables where the relationship is not a straight line. It involves finding the best parameters for a nonlinear equation that minimizes the difference between observed and predicted data points, often using iterative algorithms like the Levenberg-Marquardt method or gradient descent.