The best line fit can be found analytically by the least squares method. So can we say that linear regression (least squares) has an optimizer?
For example, for logistic regression I can use an optimizer, gradient descent. But for linear regression, where the best model parameters can be found analytically, does it make sense to say that I use an optimizer? An optimizer in general can be any algorithm that takes as input a model, model parameters, evaluator (function that tells you how good particular parameters are), and produces as output the best model parameters.