Least squares optimization is a mathematical method used to find the best-fitting curve or line to a given set of data by minimizing the sum of the squares of the differences between the observed and predicted values. It is widely used in regression analysis to estimate the parameters of a model, ensuring that the overall error between predicted and actual outcomes is minimized.