This is a trivial linear model, where you don't even fit the weights of the model, but instead use the constant values. Linear models make deficision using
cl(x) = sgn(<w,x>+b) = sgn( SUM w_i x_i + b )
where x is your data point (x_i is ith feature). In your case, all w_i=1 (you just add all the features, that's all). Callin this "theorem" would be too much, it is just a priori assumed (as you do not train it) trivial (as it consists of constant values, no expert knowledge) linear model (as it uses weighted sum of features).