Why is Linear Regression called a linear model even when features are non-linear?

It is linear in parameters, not necessarily in input features.

Linear regression refers to linearity in coefficients β. You can apply transformations like x², log(x), or interactions, but the model remains linear in β, allowing convex optimization and closed-form solutions.