Nonlinear Least Squares is a form of regression analysis used to fit a set of observations with a model that is nonlinear in its parameters, minimizing the sum of the squares of the differences between the observed and predicted values. It is widely used in scientific and engineering applications where models are inherently nonlinear, requiring iterative optimization techniques for parameter estimation.