Unseen classes - 'Other' class or classifying based on the existing classes
You could definitely add more samples and tag it as other with your classifier. However, realistically this might not be an option. For this exact purpose, you could use confidence values with the output of your classifier to predict the "other" class. You could bring in confidence thresholding to support this, i.e if your classifier is not confident > 0.8 (as an example) with its prediction, then you tag it "other" class. 

What is the best value to threshold with, you can identify by running a number of experiments with different threshold values and plot a graph for correctness i.e classification error rate graph.