Knowledge of prior probability is required to solve this problem. Consider the proposition:
\begin{align}
N_k\equiv\textrm{There are $k$ number of white balls; }0\leq k\leq n
\end{align}
I shall assume uniform probability for number of white balls i.e.
\begin{align}
P(N_0)=P(N_1)=P(N_2)=...=P(N_n)=\frac{1}{n+1}
\end{align}
Now consider the proposition:
\begin{align}
W_j\equiv\textrm{$j$-th pick (without replacement) is a white ball; }1\leq j\leq n
\end{align}
In what follows product of propositions stands for logical AND between them. What you need is $P(N_k|W_1W_2)$ which is the probability that $i$ number of balls are white given that first two picks without replacement were both white.
It is easier to calculate the reverse probabilities:
\begin{align}
P(W_1|N_k)& =\frac{k}{n},\quad 0\leq k\leq n\\
P(W_2|W_1N_k)& =\frac{k-1}{n-1},\quad 1\leq k\leq n\\
P(W_2W_1|N_k) & = P(W_2|W_1N_k)P(W_1|N_k)=\frac{k(k-1)}{n(n-1)},\quad 0\leq k\leq n\\
P(W_1W_2)& =\sum_{k=0}^nP(N_k)P(W_2W_1|N_k)=\frac{1}{n+1}\sum_{k=2}^n\frac{k(k-1)}{n(n-1)}=\frac{1}{3}
\end{align}
where in the third and fourth equations I have used Bayes theorem to split up the probabilities.
Thus:
\begin{align}
P(N_kW_1W_2) & =P(W_1W_2)P(N_k|W_1W_2)=P(N_k)P(W_1W_2|N_k)\\
P(N_k|W_1W_2)&=\frac{P(N_k)P(W_1W_2|N_k)}{P(W_1W_2)}\\
&=\frac{3k(k-1)}{n(n-1)(n+1)}
\end{align}
Above is a monotonic increasing function of $k$. Therefore $k=n$ has the highest probability, equal to $3/(n+1)$. I don't know what your definition of "most probably" is, but in this problem most probable number of white balls is equal to the total number of balls $n$.