Formal definition for parameter setting in data mining context
First part about parameter setting regards to the fact that you don't need to define any parameters of the model, which is the case in per se linear regression which takes the form of ŷ =θ0+θ1x where $θ_0,θ_1$ are parameters. Decision trees create those n-dimensional boundaries for future classification (regression) based on certain criteria. 

If you are familiar with statistical inference, a good analogy would be good old parametric vs non-parametric tests.