Modeling inclusive fitness
Generalities

There are plenty of ways at looking at phenotypes that affect the fitness of the carrier and of other individuals. One of them is group selection and another one is kin selection. Those two concepts are just two different ways of looking at the same processes. Now let's consider only the kin selection way of looking at these processes.

You can either consider the impact of the phenotype of a focus individual to neighbour individuals or the impact of neighbour individuals to the focus individual. Looking at it both ways, would yield to count the effect of your phenotype on twice. It doesn't make much sense to talk about the mean inclusive fitness of a population. You can only talk about the mean fitness of a population.

The confusion

The reason for all these confusion boils down to what $B$ and $C$ really mean. One of the issue is that you confuse $B$ and $b$, $C$ and $c$. The formulation $rB&gt;C$ is a oversimplification of the reality. Hamilton did not use this formulation at first and interpreting $b$ as the benefit for the carrier might be misleading. It is important to understand Hamilton's rule in its original formulation and it is important to understand the evolutionary game theory that underlies the evolution of social traits.

What is Hamilton's rule

One cannot study the evolution of social traits under the kin selection framework if (s)he doesn't understand the underlying game theory. $rB&gt;C$ assumes that the game we're playing is the Prisoner's dilemna. You can learn more about game theory. You can learn more about evolutionary game theory on wiki or in this book. Here is a Khan academy video on Prisoner's dilemna

Let's assume we are playing prisoner's dilemna. The fitness of an individual which cooperate is by definition $w_o + b - c$ (note the letters are not capitalized). If you cooperate and the other don't, your fitness is $w_o - c$. If you don't cooperate and the other does cooperate, you fitness is $w_o + b$. If nobody cooperates, your fitness if $w_o$. And by definition , $b&gt;c$. Knowing the frequency of people that cooperate in the population $y$ and knowing and your probability of cooperating is $x$. Then, the level of altruism (frequency of cooperations) increases in the population if and only if 

$$R\cdot\frac{dw(x,y)}{dx}&gt;\frac{dw(x,y)}{dy}$$, where $R$ is the coefficient of relatedness which can itself be expressed as a correlation between the variables $x$ and $y$. $w(x,y)$ is the fitness of the the individual being altruistic with probability $x$ in a population where individuals cooperate with probability $y$ and $\frac{dw(x,y)}{dx}$ is the partial derivative of the fitness function with respect to $x$. By definition, $\frac{dw(x,y)}{dx} = B$ and $\frac{dw(x,y)}{dy}=C$ (capital letters).

The mean fitness of the population therefore depends on the frequency of cooperation $y$. Let's assume for simplicity that $y=1$ (equilibrium), then the mean fitness of the population is $w_o + b - c$ (note that the letters, $b$ and $c$ are not capital letter), and the variance in fitness is null. All individuals has a fitness of $w_o + b -c$ as all individuals are altruistic and perform action that has a negative impact on the fitness $-c$ and a positive impact on their fitness $b$.

In short

$b$ and $c$ in your question, correspond to $b$ and $c$ in my answer and not to $B$ and $C$. If you're playing prisoner's dilemna, then by definition, if everybody cooperate (no variance in the population), then everybody has a fitness of $w_o + b - c$ and the mean fitness is $w_0 + b - c$ (as there is no variance). Now the question of whether everybody ends up cooperating depends on $B$, $C$ and $R$.

In your edit, you write $rb$ and $c$ but you get confused about the meaning of $b$ and $c$. If you are playing prisoner's dilemna, when you cooperate with someone that is also cooperating, you inclusive fitness is $b-c + r(b-c)$ and if you cooperate with someone that is not cooperating, your inclusive fitness is $b-c + r(b)$.