I'm not clear on where the confusion lies, but here's an example. Let's suppose that you want to match on age, income, and gender. In the logistic regression PSM approach, it estimates the probability of a case as a model with those three variables, so the matches are based on closeness of the predicted probabilities computed from those variables weighted by the logistic regression coefficients (transformed through the logit function). So differences in the predictors increase the difference in the predicted probabilities for the pair and make matching those cases less likely, but there is no maximum difference in the input variables beyond which a match is not allowed.
With the CCM procedure, instead, you specify the bounds for the match based on differences in those three variables. For example, you might specify
1 500 0
where 1 is the maximum age difference, 500 is the income difference and 0 indicates exact match on gender. You enter those three values in the match tolerances field separated by blanks in the same order as the variables are entered.
Any case-control comparison where any of the variable differences are outside the specified bound in either direction are not eligible for a match. Then the difference is computed for each eligible pair, and the control with the smallest differences among the available cases is assigned as the match. The exact formulas for computing the difference are detailed in the dialog and syntax help. There are three possible distance measures that you select from on the Options subdialog.
For multiple matches, this process is repeated as many times as there are names in the Names for Match variables field, taking into account whether sampling with or without replacement. The names are entered in that field separated by blanks.
I hope that clears things up.