There is a lot of stuff on the forums about walk forward to read. In its basic format walk forward is that you develop your system on a section of in sample data and then forward test it on a different section of different data to see if it still works or fails. Then there is walk forward with optimisation of variables and this really just shows you which set of values worked best on each set of in sample and out of sample data if you break the data that you have down into many smaller segments. If all the values are the same then ‘Bingo!’ you (might) have hit the jackpot and those same values might just work in the future too. If they vary wildly then you are most likely curve fitted.

That is a very basic description of walk forward testing!