Text mining is the extraction of information from unstructured, electronically accessible text resources. It is a particularly important area of bioinformatics because of the vast size of the scientific literature. A nice example of a useful application created via text mining is called
iHOP - information Hyperlinked Over Proteins. iHOP was produced by identifying thousands of protein names in
PubMed documents and then linking the documents that shared proteins together. This makes it possible to 1) quickly display most of the relevant textual information about a particular protein in one location and 2) browse the literature by "hopping" from paper to paper along gene-based hyperlinks.
In a way, every time you do a search on Google or on PubMed you are doing a little text mining, but the field is generally concerned with more automated methods for extracting knowledge from large sources of unstructured (no XML tags, not a database..) text.