Model-based selection keeps the variables that an estimator considers useful: nonzero Lasso coefficients, importances from a tree or forest, or recursive elimination (RFE). It accounts for the model, but depends on its quality and must be done in the pipeline, with cross-validation.
Example
SelectFromModel(Lasso(alpha=0.01))