Do some counting:

1. Count the number of TF binding sites in genes-of-interest (or their promoters, etc.).
2. Count the number of genes-of-interest.
3. Count the number of TF binding sites in all genes (or, again, their promoters, etc.).
4. Count the number of total genes.

Look up the hypergeometric test in R via ?phyper.

The phyper() function takes at least four arguments:

1. q: The number of white balls drawn without replacement from an urn which contains both black and white balls.
2. m: The number of white balls in the urn.
3. n: The number of black balls in the urn.
4. k: The number of balls drawn from the urn.

In this case, q is the number of TF binding sites in the genes-of-interest. The m is the number of TF binding sites in all genes. The n is the number of TF binding sites in genes that are not TF binding sites in genes-of-interest (subtract the count of sites in genes-of-interest from the count of sites in genes). The k is the count of genes-of-interest.

The resulting p-value should indicate the likelihood of observing q or fewer TF sites in genes-of-interest by chance, relative to TF sites over all genes. If that value is less than a pre-decided threshold (say 0.01) then you could argue this suggests enrichment for those particular TF sites.

If it's human or mouse, you could try using this