How to collect info about unseen bugs given user's comments/feedbacks?
It sounds like you are looking for an unsupervised learning approach (meaning you don't need to manually label your data).
Something like k-means clustering could work well. This would allow you to group you comments into k distinct clusters. You could then view counts of comments in those clusters and explore the clusters to determine their meaning.
In order to perform the clustering, you need to transform your data from text to a numerical vector space. A common approach would be tf-idf, but you may find that something else works better.
Since you mentioned Python, both k-means and tf-idf can be accomplished using sklearn:

sklearn.cluster.KMeans
sklearn.feature_extraction.text.TfidfVectorizer

There's a pretty nice example of k-means clustering using tf-idf on Kaggle.