What is the common name for the regularization technique that adds the squared magnitude of coefficients as a penalty term to the loss function?

L2 regularization (or Ridge regression)

Also known as Ridge Regression or Tikhonov regularization, L2 regularization penalizes large weights by adding a term proportional to the sum of their squares. This encourages the model to spread the weights more evenly across features.