nested CV feature selection
Assuming the feature selection method is always the same, on an external data (or final training set), you would simply apply the exact same method. The actual set of selected features does not matter.
If there was any difference in the selection method, for instance if you are selecting different number of features, you would do like with any other hyper-parameter: select the best model according to the nested CV process, then apply the same hyper-parameters (including for instance number of features) when training the final model.