Probably you are use words to differentiate two major groups of methods used in data-mining.

Clustering methods is often used when you have data and would like to classify it without know the labels. So these algorithms will split the data into groups where the points belongs to a group are more similar than the points in different groups.

This kind of task is know as unsupervised learning.

Classification methods in the other hand are used to classify a data set where you know the labels. We could also divide this in tow major groups regression (for continuous outcomes) our classification (categorical outcomes). These kind of task are know as supervised learning.

They maintain several similarities, since they consider the same problema of diffrent perspective

I think this link will be useful:

http://www.differencebetween.net/technology/difference-between-clustering-and-classification/