Multicollinearity in regression must be addressed — variables should be removed until the multicollinearity is gone.
Multicollinearity is not such a problem for trees, clustering and nearest-neighbours methods. In these methods, it may be advisable to retain p dummy variables. However, even in these methods, non-redundancy in predictor variables is still desired.