Least Squares is a mathematical optimization technique used to find the best-fitting curve or line to a given set of data points by minimizing the sum of the squares of the differences between the observed and predicted values. It is widely used in regression analysis and curve fitting to ensure that the model has the least possible error in predicting the dependent variable from the independent variables.