If their exist structural breaks in your data, which might alter the parameters that produce the data, then you may want to cut out the data before that structural break occurred so that you can forecast with the correct parameters.
If you notice a seasonal pattern 10 years ago that you know has died out, you may also want to cut out that data to simplify modeling.
For example, if it's air traffic you're modeling, you may want to cut out the period before 9-11. Also, I suspect there is an transient intervention in the current period, caused by Covid-19, which will probably mess up forecasts going forward until airport travel stabilizes when (if) the virus passes.
Others on this site may be able to give you a much more detailed answer