In a narrow sense, the Least Squares Method is a technique for fitting a straight line through a set of points in such a way that the sum of the squared vertical distances from the observed points to the fitted line is minimized.
In a wider sense, the Least Squares Method is a general approach to fitting a model of the data-generating mechanism to the observed data. The model is specified by an equation with free parameters. The values of the model parameters are being chosen to minimize the sum of the squared deviations of the data from the values predicted by the model.
The Least Squares Method is widely used in building estimators and in regression analysis.