boxconstraint of function svmtrain

Does anyone know about "boxconstraint" of function "svmtrain"?

The website says that:

Value of the box constraint C for the soft margin. C can be a scalar, or a vector of the same length as the training data. If C is a scalar, it is automatically rescaled by N/(2*N1) for the data points of group one and by N/(2*N2) for the data points of group two, where N1 is the number of elements in group one, N2 is the number of elements in group two, and N = N1 + N2. This rescaling is done to take into account unbalanced groups, that is cases where N1 and N2 have very different values. If C is an array, then each array element is taken as a box constraint for the data point with the same index.

But I have some question about this

1. group one means the group attributes to 0 or 1?
2. If the definition is like it says1<C< unlimited， but why C can be set to 0.1?